This paper is in the following e-collection/theme issue:

Decision Support for Health Professionals (1500) Artificial Intelligence (2044) Clinical Information and Decision Making (1860) Secondary Use of Clinical Data for Research and Surveillance (463)

Published on in Vol 8, No 10 (2020): October

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/18287, first published .
Construction of a Digestive System Tumor Knowledge Graph Based on Chinese Electronic Medical Records: Development and Usability Study

Construction of a Digestive System Tumor Knowledge Graph Based on Chinese Electronic Medical Records: Development and Usability Study

Construction of a Digestive System Tumor Knowledge Graph Based on Chinese Electronic Medical Records: Development and Usability Study

Authors of this article:

Xiaolei Xiu1 Author Orcid Image ;   Qing Qian1 Author Orcid Image ;   Sizhu Wu1 Author Orcid Image
Article Authors Cited by (18) Tweetations (1) Metrics

Journals

  1. Guo L, Tang Y, Wang Y, Xu H. Prognostic Value of lncRNA NEAT1 as a New Biomarker in Digestive System Tumors: a Systematic Study and Meta-analysis. Expert Review of Molecular Diagnostics 2021;21(1):91 View
  2. Li X, Lyu M, Wang Z, Chen C, Zheng P. Exploiting knowledge graphs in industrial products and services: A survey of key aspects, challenges, and future perspectives. Computers in Industry 2021;129:103449 View
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  4. Wu X, Duan J, Pan Y, Li M. Medical Knowledge Graph: Data Sources, Construction, Reasoning, and Applications. Big Data Mining and Analytics 2023;6(2):201 View
  5. Yuanchuan D, Hang D, Shi L, Kailin L, Yijie F. Auxiliary diagnosis study of integrated electronic medical record text and CT images. Journal of Intelligent Systems 2022;31(1):753 View
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  7. Thukral A, Dhiman S, Meher R, Bedi P. Knowledge graph enrichment from clinical narratives using NLP, NER, and biomedical ontologies for healthcare applications. International Journal of Information Technology 2023;15(1):53 View
  8. Wu Y, Min H, Li M, Shi Y, Ma A, Han Y, Gan Y, Guo X, Sun X. Effect of Artificial Intelligence-based Health Education Accurately Linking System (AI-HEALS) for Type 2 diabetes self-management: protocol for a mixed-methods study. BMC Public Health 2023;23(1) View
  9. Yang Y, Lu Y, Zheng Z, Wu H, Lin Y, Qian F, Yan W. MKG-GC: A multi-task learning-based knowledge graph construction framework with personalized application to gastric cancer. Computational and Structural Biotechnology Journal 2024;23:1339 View
  10. Cai F, He J, Liu Y, Zhang H. BCSLinker: automatic method for constructing a knowledge graph of venous thromboembolism based on joint learning. Frontiers in Medicine 2024;11 View
  11. Liu C, Li Z, Li J, Qu Y, Chang Y, Han Q, Cao L, Lin S. Research on Traditional Chinese Medicine: Domain Knowledge Graph Completion and Quality Evaluation. JMIR Medical Informatics 2024;12:e55090 View
  12. Mohammad Y, Nachouki M, Mohamed E. Knowledge Management Systems in Business Management Using Knowledge Graphs and Semantic Technologies. International Journal of Knowledge Management 2025;21(1):1 View
  13. Zhang Y, Lau R. Uncertainty Detection: A Multi-View Decision Boundary Approach Against Healthcare Unknown Intents. Applied Sciences 2025;15(13):7114 View

Conference Proceedings

  1. Yan Y, Yu P, Fang H, Wu Z. 2022 IEEE International Symposium on Broadband Multimedia Systems and Broadcasting (BMSB). Trustworthiness Measurement for Multimedia Domain Knowledge Graph View
  2. Bashir A, Nagpal R, Mehrotra D, Bala M. 2023 13th International Conference on Cloud Computing, Data Science & Engineering (Confluence). Interoperability of Electronic Health Records for Dyslipidemia using Knowledge graphs View
  3. Wu X, Wu Y, Li M. 2022 IEEE International Conference on Bioinformatics and Biomedicine (BIBM). MERAS: A method for entity recognition, alignment, and structuration from Chinese Electronic Medical Records View
  4. Wu Z, Wan Y, Ma H, Chen Q. 2023 19th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD). Construction of Knowledge Graph of Neurodegenerative Diseases Based on Ontology View
  5. Tian-Yu G, Hua-Yuan Y. 2025 6th International Conference on Computing, Networks and Internet of Things (CNIOT). UTCMKG: A Lightweight Universal Model for Constructing Traditional Chinese Medicine Case Knowledge Graphs View